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 coordination is needed to provide interoperability, end-to-end functionality, documentation and long term support; SatHub will provide a natural home for that effort. Some relevant software which already exists is noted in the report.

3.2.1. Create Test Datasets

An urgent task is to define a range of test datasets which can be used to validate the software tools that are developed. These datasets should include satellite streaks captured by instruments with a range of apertures, exposure times, pixel sizes and background characteristics. Cases where pairs of observations of the same sky region are available with and without trails will be especially useful. A test satellite ephemeris database will also be needed to exercise pass prediction tools in a controlled way.

3.2.2. Create TrailMask

The proposed TrailMask software effort needs to recognize and flag satellite trails in optical/NIR image data (spectroscopic data is a different challenge). It must handle mosaic imagers and probably also cases where the detector is dithered, and should not confuse satellite trails with asteroid trails or other valid data. Programmatic and web-based interfaces will be needed to support different user communities. TrailMask should be able to run “blind” with little prior information, or “seeded” where locations of predicted trails are input.

3.2.3. Create PassPredict

In the era when satellite trails are frequent but not ubiquitous, it will be important to know when particular astronomical targets will be affected by trails and when they are expected to be free of them. PassPredict would use a satellite ephemeris database to check when particular areas of sky will be affected by satellite passes. We concluded that the accuracy of these predictions may be good enough to say when a satellite will be in the field of view but not good enough (at least if only low-accuracy TLEs are available) to say where the trail will be in that field of view. Statistical approaches to determine areas of sky which have a lower density of trails at a given time will also be useful, and complementary to the specific predictions.

3.2.4. Create Simulation Tools

The TrailMask and PassPredict tools are aimed at the typical working observational astronomer (professional or hobbyist) trying to make specific new observations. But as a community we also need to assess the overall impact, current and future, of satellite trails on our science, and this will require significant simulation efforts. Individual observatories will also want to carry out simulations to assess impacts on their programs. We propose developing software which will create images with simulated satellite trails at various levels of fidelity, as well as software which will automatically assess collections of such images to quantify things like the percentage degradation in source detection efficiency as a function of brightness.

The Community Engagement WG aimed to engage a broad swath of diverse stakeholders in dark skies and near-Earth space beyond professional astronomy alone, who are impacted by large “mega-constellations” of tens of thousands of LEO satellite constellations. The Community Engagement WG consisted of 22 members across 23 time zones including professional and amateur astronomers, members of sovereign Indigenous/First Nations communities, dark-sky advocates, planetarium professionals, and environmental/ecological nongovernmental organizations. Community Engagement WG members conducted scores of conversations, surveys, listening sessions, outreach, and meetings with members of many constituencies and interest groups that were potentially or already impacted by LEO satellite constellations. For SATCON2, the Community Engagement WG focused on five specific constituencies, who shared their feedback, needs and recommendations at the workshop. 8
 * 1) Astrophotography and Astro-Tourism
 * 2) Amateur Astronomy
 * 3) Indigenous Communities and Perspectives
 * 4) Planetariums
 * 5) Environmental and Ecological Concerns